FleetQ vs LangGraph: a control plane next to a code library
LangGraph is a library from the LangChain team for building agents as graphs in code. FleetQ is a self-hosted platform for running agents in production: it gives every agent run an approval inbox, a budget, an audit trail and an MCP server, and you manage it from a web UI, a REST API or any MCP client.
The two are not direct substitutes. This page explains where each one fits, so you can decide whether you need one, the other, or both.
The short answer
When LangGraph is the better fit
Pick LangGraph if you want to write your agent logic as Python or JavaScript code, and you value a large ecosystem, a big community and a library that many teams have already used for a long time.
When FleetQ is the better fit
Pick FleetQ if you need the operational layer around agents: human approvals with SLAs, hard budget limits, a full activity log, bring-your-own keys and an MCP server, all self-hosted under AGPL-3.0.
FleetQ and LangGraph side by side
| Feature | FleetQ | LangGraph |
|---|---|---|
| Focus | Control plane for running AI agents in production: approvals, budgets, audit trail and MCP access around your agents. | See their docs |
| Self-hosting | Yes. AGPL-3.0 licensed, self-hosted for free with Docker Compose. | See their docs |
| Human approvals | Approval inbox with SLA enforcement and escalation, plus human tasks inside workflows. | See their docs |
| Budget limits | Credit ledger with pessimistic locks, auto-pause on overspend and project budget caps. | See their docs |
| Audit trail | Activity log of every action, searchable and filterable. | See their docs |
| MCP server | Built-in MCP server (AgentFleetServer) over HTTP/SSE and stdio. | See their docs |
| Bring-your-own LLM keys | BYOK for Anthropic, OpenAI and Google, plus local LLMs such as Ollama, LM Studio and vLLM. | See their docs |
| Pricing model | Community Edition is free to self-host. FleetQ Cloud is free to start, with paid tiers. | See their docs |
Checked on 2026-11-08. LangGraph changes over time, so its own docs are the source of truth.
Different layers of the stack
A code library is where you describe what an agent does step by step. A control plane is where you decide who may run it, what it may spend, who must approve its actions and how you can audit what happened later. FleetQ focuses on the second job. It still ships its own agents, crews and a visual workflow builder, so you can build without writing graph code, but its main value is the governance around each run.
If your team already has agents written in code, the question is usually not which tool is better, but which layer is missing. Most teams that move agents from a prototype to production find that approvals, cost limits and audit logs take more time to build than the agent itself.
What FleetQ adds when agents go to production
Every risky action can stop in an approval inbox until a person accepts or rejects it, with SLA enforcement and escalation when nobody answers in time. Spend is reserved and settled against a credit ledger with pessimistic locks, so a runaway loop pauses itself instead of draining your provider account. Every change is written to an activity log that you can search and filter.
You bring your own keys for Anthropic, OpenAI and Google, or point agents at local models through Ollama, LM Studio or vLLM. Nothing leaves your servers unless you send it.
How to choose
Start from the problem you have today. If you are still exploring how an agent should reason, a code library gives you fine control. If you already know what your agents should do and now need people, money and compliance to trust them, a control plane saves you from building that layer yourself. Check the LangGraph docs for its current features, since this table only lists what we could confirm.
Read more in the docs
Frequently asked questions
- Is FleetQ a LangGraph alternative?
- Partly. FleetQ has its own agents, crews and visual workflows, so you can build agents without LangGraph. Its focus is the production layer: approvals, budgets, audit trail and an MCP server.
- Is FleetQ open source?
- Yes. The Community Edition is licensed under AGPL-3.0 and you can self-host it for free, including for commercial use.
- Can other tools call FleetQ?
- Yes. FleetQ exposes a REST API and a built-in MCP server over HTTP/SSE and stdio, so any MCP client can create and run agents in FleetQ.
Try FleetQ your way
Self-host the AGPL-3.0 Community Edition, or start on FleetQ Cloud for free.